Special Issue "Proximal and Remote Sensing in the MWIR and LWIR Spectral Range"

A special issue of Remote Sensing (ISSN 2072-4292).

Deadline for manuscript submissions: 31 October 2021.

Special Issue Editors

Dr. Stefano Pignatti
E-Mail Website
Guest Editor
Institute of Methodologies for Environmental Analysis, National Research Council (CNR IMAA), C.da S.Loja snc, 85050 Tito (Potenza), Italy
Interests: remote sensing research in soil and vegetation; hyperspectral remote sensing
Special Issues and Collections in MDPI journals
Dr. Fabrizia Buongiorno
E-Mail Website
Guest Editor
Istituto Nazionale di Geofisica e Vulcanologia (INGV), National Earthquake Observatory, Rome, Italy
Interests: airborne and space imaging spectrometers acquiring data in the VSWIR-LWIR; technical characteristics and requirements for geophysical; geological applications; retrieval algorithms for surface temperature and volcanic gas emissions; space and ground data integration for cultural heritage preservation
Special Issues and Collections in MDPI journals
Dr. Martin Schlerf
E-Mail Website
Guest Editor
Senior Research Associate, Luxembourg Institute of Science and Technology (LIST), 5, avenue des Hauts-Fourneaux, L-4362 Esch/Alzette, Luxembourg
Interests: hyperspectral and thermal remote sensing; retrieval of biochemical and structural vegetation properties; water stress detection; crop nitrogen assessment
Special Issues and Collections in MDPI journals
Dr. Angelo Palombo
E-Mail Website
Guest Editor
Institute of Methodologies for Environmental Analysis CNR-IMAA, C.da S. Loja s.n.c, 85050 Tito, Italy
Interests: thermal remote sensing; sensor calibration and validation
Dr. Simon J. Hook
E-Mail Website
Guest Editor
Jet Propulsion Laboratory, 4800 Oak Grove Drive , Pasadena, CA 91109, USA
Interests: expert on optical radiometry, in particular thermal infrared spectroscopy, ECOSTRESS Principal Investigator

Special Issue Information

Dear Colleagues,

IR (MWIR (Mid-Wave Infrared) 3–5 µm and LWIR (Long-Wave Infrared) 7–12 µm) sensing technologies have reached a significant level of maturity, and have become a powerful method of Earth surface sensing.

Thermal sensing is currently used to characterize Land Surface Temperature (LST), Land Surface Emissivity (LSE), and many other environmental proxy variables, some of which can have a further relevance when assimilated into hydrological and climatological models.

The usefulness of IR sensing has been tested in many environmental applications and also in the spatio-temporal domain for the identification of spatial patterns.

This Special Issue intends to collect the major contributions of the EGU session as well as manuscripts dealing with the actual and future IR imagery, from broadband to multi/hyperspectral (ECOSTRESS, ASTER, Sentinel3, Landsat, etc., and airborne sensors), and the application of proximal or remote sensing data in the following specific research themes:

  • IR instruments solution
  • Instrument radiometric calibration procedures
  • Algorithms retrieval for LST and emissivity
  • Soil properties characterization
  • Evapotranspiration, plant water stress, and drought
  • IR targets identification
  • Archaeological prospection
  • Urban areas and infrastructure investigation
  • Geophysical phenomena characterization
  • IR synergy with optical imagery

Dr. Stefano Pignatti
Dr. Fabrizia Buongiorno
Dr. Eyal Bendor
Dr. Martin Schlerf
Dr Angelo Palombo
Dr. Simon J. Hook
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • IR payloads and mission
  • LST and LSE algorithms
  • IR Earth surface sensing
  • Thermal airborne/UAV applications
  • IR geophysical parameter retrieval

Published Papers (7 papers)

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Research

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Article
The DLR FireBIRD Small Satellite Mission: Evaluation of Infrared Data for Wildfire Assessment
Remote Sens. 2021, 13(8), 1459; https://doi.org/10.3390/rs13081459 - 09 Apr 2021
Viewed by 528
Abstract
Wildfires significantly influence ecosystem patterns and processes on a global scale. In many cases, they pose a threat to human lives and property. Through greenhouse gas emissions, wildfires also directly contribute to climate change. The monitoring of such events and the analysis of [...] Read more.
Wildfires significantly influence ecosystem patterns and processes on a global scale. In many cases, they pose a threat to human lives and property. Through greenhouse gas emissions, wildfires also directly contribute to climate change. The monitoring of such events and the analysis of acquired data is crucial for understanding wildfire and ecosystem interactions. The FireBIRD small satellite mission, operated by the German Aerospace Center (DLR), was specifically designed for the detection of wildfires. It features a higher spatial resolution than available with other Earth-observation systems. In addition to the detection of active fire locations, the system also allows the derivation of fire intensity by means of the Fire Radiative Power (FRP). This indicator can be used as a basis to derive the amount of emitted pollutant, which makes it valuable for climate studies. With the FireBIRD mission facing its end of life in 2021, this study retrospectively evaluates the performance of the system through an inter-comparison with data from two satellite missions of the National Aeronautics and Space Administration (NASA) and discusses the potential of such a system. The comparison is performed regarding both geometrical and radiometric aspects, the latter focusing on the FRP. This study uses and compares two different methods to derive the FRP from FireBIRD data. The data are analyzed regarding six major fire incidents in different regions of the world. The FireBIRD results are in accordance with the reference data, showing a geometrical overlapping rate of 83% and 84% regarding MODIS (Moderate-resolution Imaging Spectroradiometer) and VIIRS (Visible Infrared Imaging Radiometer Suite) overpasses in close temporal proximity. Furthermore, the results show a positive bias in FRP of about 11% compared to MODIS. Full article
(This article belongs to the Special Issue Proximal and Remote Sensing in the MWIR and LWIR Spectral Range)
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Article
An Exploratory Study on the Effect of Petroleum Hydrocarbon on Soils Using Hyperspectral Longwave Infrared Imagery
Remote Sens. 2019, 11(5), 569; https://doi.org/10.3390/rs11050569 - 08 Mar 2019
Cited by 4 | Viewed by 1836
Abstract
Manmade crude oil contamination, which has negative impacts on the environment and human health, can be found in various ecosystems all over the globe. Hyperspectral remote sensing (HRS) is an efficient tool to investigate this crude oil contamination where its electromagnetic spectrum is [...] Read more.
Manmade crude oil contamination, which has negative impacts on the environment and human health, can be found in various ecosystems all over the globe. Hyperspectral remote sensing (HRS) is an efficient tool to investigate this crude oil contamination where its electromagnetic spectrum is analyzed. This exploratory study used an innovative HRS imagery sensor to study the effect of petroleum hydrocarbon (PHC), found in crude oil, on the spectrum of soils across the longwave infrared (LWIR 8–12 μm) spectral region. This contrasts with previous studies that focused on shortwave and midwave infrared (SWIR 1–2.5 and MWIR 3–8 μm, respectively) regions. An outdoor HRS image of three different types of soils, contaminated with 11 PHC concentrations, was processed and analyzed. Since PHC is spectrally featureless in the LWIR region, the analysis focused on the spectral alteration of the dominant minerals in the soils. Good evaluation metrics of R2 > 0.83 and a root-mean-squared-error (RMSE) between 1.06 and 1.33 wt % showed that the PHC level can be predicted with relatively good accuracy, even without direct spectral features of crude oil PHC, using an airborne LWIR camera in field conditions. This study can be used as a proof of concept for future airborne remote sensing of PHC-contaminated soils. Full article
(This article belongs to the Special Issue Proximal and Remote Sensing in the MWIR and LWIR Spectral Range)
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Technical Note
Monitoring of Surface Temperature on Parco delle Biancane (Italian Geothermal Area) Using Optical Satellite Data, UAV and Field Campaigns
Remote Sens. 2020, 12(12), 2018; https://doi.org/10.3390/rs12122018 - 24 Jun 2020
Cited by 4 | Viewed by 1009
Abstract
The purpose of this study is to analyze the surface temperature and the distribution of thermal signatures on Tuscany’s geothermal districts using data obtained through three separate surveys via satellite and an unmanned aerial vehicle (UAV). The analysis considers the highest available spatial [...] Read more.
The purpose of this study is to analyze the surface temperature and the distribution of thermal signatures on Tuscany’s geothermal districts using data obtained through three separate surveys via satellite and an unmanned aerial vehicle (UAV). The analysis considers the highest available spatial resolution ranging from hundreds of meters per pixel of the satellite thermal images and the tenths/hundreds of centimeters per pixel of the thermal images acquired by the UAV. The surface temperature maps obtained by satellite data acquired at suitable spatial resolution and the thermal measurements obtained by the thermal camera installed on the UAV were orthorectified and geocoded. This allowed, for example, following the evolution of thermal anomalies, which may represent a modification of the current state of the geothermal field and a possible hazard for both the population and industrial assets. Here, we show the results obtained in three field campaigns during which the simultaneous acquisition of Landsat 8 satellite and UAV (FlyBit octocopter, IDS, Rome, Italy) thermal data were analyzed. By removing the atmosphere contribution from Landsat 8 data, we have produced three surface temperature maps that are compared with the ground field measurements and the surface temperature maps elaborated by FLIR VUE PRO-R on the UAV. Full article
(This article belongs to the Special Issue Proximal and Remote Sensing in the MWIR and LWIR Spectral Range)
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Technical Note
Application of Hyperspectral Remote Sensing in the Longwave Infrared Region to Assess the Influence of Dust from the Desert on Soil Surface Mineralogy
Remote Sens. 2020, 12(9), 1388; https://doi.org/10.3390/rs12091388 - 28 Apr 2020
Cited by 1 | Viewed by 869
Abstract
Soil mineralogy can be used to study changes in the environment affecting the soil surface, such as dust from the desert through Aeolian processes, which is one of the sources that determine the mineral nature of the soil. Ground- and field-based hyperspectral longwave [...] Read more.
Soil mineralogy can be used to study changes in the environment affecting the soil surface, such as dust from the desert through Aeolian processes, which is one of the sources that determine the mineral nature of the soil. Ground- and field-based hyperspectral longwave infrared images, acquired before and after dust dispersion on the soil surface, were processed and analyzed by applying a procedure for determining soil surface mineralogy from the emissivity spectrum, using two indices―SQCMI (the Soil Quartz Clay Mineral Index) and SCI (the Soil Carbonate Index)―to identify changes in the abundance of quartz, clay minerals and carbonates on the surface, caused by the settling dust particles. Mineralogical changes were identified, depending on the mineral composition of the dust compared to the soil surface mineralogy. Full article
(This article belongs to the Special Issue Proximal and Remote Sensing in the MWIR and LWIR Spectral Range)
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Technical Note
First Comparisons of Surface Temperature Estimations between ECOSTRESS, ASTER and Landsat 8 over Italian Volcanic and Geothermal Areas
Remote Sens. 2020, 12(1), 184; https://doi.org/10.3390/rs12010184 - 04 Jan 2020
Cited by 13 | Viewed by 1514
Abstract
The ECO System Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) is a new space mission developed by NASA-JPL which launched on July 2018. It includes a multispectral thermal infrared radiometer that measures the radiances in five spectral channels between 8 and 12 [...] Read more.
The ECO System Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) is a new space mission developed by NASA-JPL which launched on July 2018. It includes a multispectral thermal infrared radiometer that measures the radiances in five spectral channels between 8 and 12 μm. The primary goal of the mission is to study how plants use water by measuring their temperature from the vantage point of the International Space Station. However, as ECOSTRESS retrieves the surface temperature, the data can be used to measure other heat-related phenomena, such as heat waves, volcanic eruptions, and fires. We have cross-compared the temperatures obtained by ECOSTRESS, the Advanced Spaceborne Thermal Emission and Reflectance radiometer (ASTER) and the Landsat 8 Thermal InfraRed Sensor (TIRS) in areas where thermal anomalies are present. The use of ECOSTRESS for temperature analysis as well as ASTER and Landsat 8 offers the possibility of expanding the availability of satellite thermal data with very high spatial and temporal resolutions. The Temperature and Emissivity Separation (TES) algorithm was used to retrieve surface temperatures from the ECOSTRESS and ASTER data, while the single-channel algorithm was used to retrieve surface temperatures from the Landsat 8 data. Atmospheric effects in the data were removed using the moderate resolution atmospheric transmission (MODTRAN) radiative transfer model driven with vertical atmospheric profiles collected by the University of Wyoming. The test sites used in this study are the active Italian volcanoes and the Parco delle Biancane geothermal area (Italy). In order to test and quantify the difference between the temperatures retrieved by the three spaceborne sensors, a set of coincident imagery was acquired and used for cross comparison. Preliminary statistical analyses show a very good agreement in terms of correlation and mean values among sensors over the test areas. Full article
(This article belongs to the Special Issue Proximal and Remote Sensing in the MWIR and LWIR Spectral Range)
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Letter
A Sensitivity Study of the 4.8 µm Carbon Dioxide Absorption Band in the MWIR Spectral Range
Remote Sens. 2020, 12(1), 172; https://doi.org/10.3390/rs12010172 - 03 Jan 2020
Cited by 6 | Viewed by 1078
Abstract
The measurements of gas concentrations in the atmosphere are recently developed thanks to the availability of gases absorbing spectral channels in space sensors and strictly depending on the instrument performances. In particular, measuring the sources of carbon dioxide is of high interest to [...] Read more.
The measurements of gas concentrations in the atmosphere are recently developed thanks to the availability of gases absorbing spectral channels in space sensors and strictly depending on the instrument performances. In particular, measuring the sources of carbon dioxide is of high interest to know the distribution, both spatial and vertical, of this greenhouse gas and quantify the natural/anthropogenic sources. The present study aims to understand the sensitivity of the CO2 absorption band at 4.8 µm to possibly detect and measure the spatial distribution of emissions from point sources (i.e., degassing volcanic plumes, fires, and industrial emissions). With the aim to define the characteristics of future multispectral imaging space radiometers, the performance of the CO2 4.8 µm absorption band was investigated. Simulations of the “Top of Atmosphere” (TOA) radiance have been performed by using real input data to reproduce realistic scenarios on a volcanic high elevation point source (>2 km): actual atmospheric background of CO2 (~400 ppm) and vertical atmospheric profiles of pressure, temperature, and humidity obtained from probe balloons. The sensitivity of the channel to the CO2 concentration has been analyzed also varying surface temperatures as environmental conditions from standard to high temperature. Furthermore, response functions of operational imaging sensors in the middle wave infrared spectral region were used. The channel width values of 0.15 µm and 0.30 µm were tested in order to find changes in the gas concentration. Simulations provide results about the sensitivity necessary to appreciate carbon dioxide concentration changes considering a target variation of 10 ppm in gas column concentration. Moreover, the results show the strong dependence of at-sensor radiance on the surface temperature: radiances sharply increase, from 1 Wm−2sr−1µm−1 (in the “standard condition”) to >1200 Wm−2sr−1µm−1 (in the warmest case) when temperatures increase from 300 to 1000 K. The highest sensitivity has been obtained considering the channel width equal to 0.15 µm with noise equivalent delta temperature (NEDT) values in the range from 0.045 to 0.56 K at surface temperatures ranging from 300 to 1000 K. Full article
(This article belongs to the Special Issue Proximal and Remote Sensing in the MWIR and LWIR Spectral Range)
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Letter
Mineral Classification of Soils Using Hyperspectral Longwave Infrared (LWIR) Ground-Based Data
Remote Sens. 2019, 11(12), 1429; https://doi.org/10.3390/rs11121429 - 16 Jun 2019
Cited by 4 | Viewed by 1572
Abstract
Soil mineralogy is an important factor affecting chemical and physical processes in the soil. Most common minerals in soils—quartz, clay minerals and carbonates—present fundamental spectral features in the longwave infrared (LWIR) region. The current study presents a procedure for determining the soil mineralogy [...] Read more.
Soil mineralogy is an important factor affecting chemical and physical processes in the soil. Most common minerals in soils—quartz, clay minerals and carbonates—present fundamental spectral features in the longwave infrared (LWIR) region. The current study presents a procedure for determining the soil mineralogy from the surface emissivity spectrum. Ground-based hyperspectral LWIR images of 90 Israeli soil samples were acquired with the Telops Hyper-Cam sensor, and the emissivity spectrum of each sample was calculated. Mineral-related emissivity features were identified and used to create indicants and indices to determine the content of quartz, clay minerals, and carbonates in the soil in a semi-quantitative manner—from more to less abundant minerals. The resultant mineral content was in good agreement with the mineralogy derived from chemical analyses. Full article
(This article belongs to the Special Issue Proximal and Remote Sensing in the MWIR and LWIR Spectral Range)
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